Sample (Train Data) Credit Scoring Profiling Report

Dataset statistics

Number of variables	24
Number of observations	73,799
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	14.1 MiB
Average record size in memory	200.0 B

Variable types

Numeric	8
Categorical	15
DateTime	1

Warnings

`sample` has constant value "1"	Constant
`sna` is highly correlated with `first_time`	High correlation
`first_time` is highly correlated with `sna`	High correlation
`car` is highly correlated with `car_type`	High correlation
`car_type` is highly correlated with `car`	High correlation
`home_address_1` is highly correlated with `home_address_2` and 2 other fields	High correlation
`home_address_2` is highly correlated with `home_address_1` and 2 other fields	High correlation
`work_address_2` is highly correlated with `home_address_1` and 2 other fields	High correlation
`work_address_3` is highly correlated with `home_address_1` and 2 other fields	High correlation
`car` is highly correlated with `car_type`	High correlation
`car_type` is highly correlated with `car`	High correlation
`home_address_1` is highly correlated with `home_address_2` and 2 other fields	High correlation
`home_address_2` is highly correlated with `home_address_1` and 2 other fields	High correlation
`work_address_2` is highly correlated with `home_address_1` and 2 other fields	High correlation
`work_address_3` is highly correlated with `home_address_1` and 2 other fields	High correlation
`car` is highly correlated with `car_type`	High correlation
`car_type` is highly correlated with `car`	High correlation
`home_address_1` is highly correlated with `home_address_2` and 2 other fields	High correlation
`home_address_2` is highly correlated with `home_address_1` and 2 other fields	High correlation
`work_address_2` is highly correlated with `home_address_1` and 2 other fields	High correlation
`work_address_3` is highly correlated with `home_address_1` and 2 other fields	High correlation
`work_address_3` is highly correlated with `work_address_2` and 3 other fields	High correlation
`work_address_2` is highly correlated with `work_address_3` and 2 other fields	High correlation
`car` is highly correlated with `car_type`	High correlation
`home_address_1` is highly correlated with `work_address_3` and 3 other fields	High correlation
`first_time` is highly correlated with `sna`	High correlation
`car_type` is highly correlated with `car`	High correlation
`sna` is highly correlated with `first_time`	High correlation
`work_address_1` is highly correlated with `work_address_3` and 2 other fields	High correlation
`home_address_2` is highly correlated with `work_address_3` and 3 other fields	High correlation
`sna` is highly correlated with `sample`	High correlation
`work_address_3` is highly correlated with `sample` and 3 other fields	High correlation
`sample` is highly correlated with `sna` and 13 other fields	High correlation
`work_address_2` is highly correlated with `work_address_3` and 3 other fields	High correlation
`car` is highly correlated with `sample` and 1 other fields	High correlation
`work_address_1` is highly correlated with `sample`	High correlation
`home_address_3` is highly correlated with `sample`	High correlation
`foreign_passport` is highly correlated with `sample`	High correlation
`home_address_1` is highly correlated with `work_address_3` and 3 other fields	High correlation
`home_address_2` is highly correlated with `work_address_3` and 3 other fields	High correlation
`default` is highly correlated with `sample`	High correlation
`first_time` is highly correlated with `sample`	High correlation
`sex_male` is highly correlated with `sample`	High correlation
`car_type` is highly correlated with `sample` and 1 other fields	High correlation
`good_work` is highly correlated with `sample`	High correlation
`client_id` is uniformly distributed	Uniform
`client_id` has unique values	Unique
`decline_app_cnt` has 61214 (82.9%) zeros	Zeros
`bki_request_cnt` has 19381 (26.3%) zeros	Zeros

Reproduction

Analysis started	2021-07-04 07:33:55.775719
Analysis finished	2021-07-04 07:34:48.545526
Duration	52.77 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

client_id
Real number (ℝ_≥0)

UNIFORM
UNIQUE

Distinct	73799
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	55137.96509

Minimum	1
Maximum	110147
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 MiB

Quantile statistics

Minimum	1
5-th percentile	5469.9
Q1	27440.5
median	55274
Q3	82758.5
95-th percentile	104666.1
Maximum	110147
Range	110146
Interquartile range (IQR)	55318

Descriptive statistics

Standard deviation	31841.92117
Coefficient of variation (CV)	0.5774953993
Kurtosis	-1.203837426
Mean	55137.96509
Median Absolute Deviation (MAD)	27663
Skewness	-0.003625146989
Sum	4069126686
Variance	1013907944
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2049	1	< 0.1%
85187	1	< 0.1%
85507	1	< 0.1%
83458	1	< 0.1%
87552	1	< 0.1%
42494	1	< 0.1%
48637	1	< 0.1%
46588	1	< 0.1%
36347	1	< 0.1%
34298	1	< 0.1%
Other values (73789)	73789	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
10	1	< 0.1%
11	1	< 0.1%
12	1	< 0.1%

Value	Count	Frequency (%)
110147	1	< 0.1%
110146	1	< 0.1%
110145	1	< 0.1%
110143	1	< 0.1%
110142	1	< 0.1%
110141	1	< 0.1%
110140	1	< 0.1%
110139	1	< 0.1%
110138	1	< 0.1%
110137	1	< 0.1%

score_bki
Real number (ℝ)

Distinct	69096
Distinct (%)	93.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-1.904723627

Minimum	-3.62458632
Maximum	0.19977285
Zeros	0
Zeros (%)	0.0%
Negative	73790
Negative (%)	> 99.9%
Memory size	1.1 MiB

Quantile statistics

Minimum	-3.62458632
5-th percentile	-2.695736607
Q1	-2.259533835
median	-1.92082293
Q3	-1.56983126
95-th percentile	-1.05476331
Maximum	0.19977285
Range	3.82435917
Interquartile range (IQR)	0.689702575

Descriptive statistics

Standard deviation	0.4982310572
Coefficient of variation (CV)	-0.2615765616
Kurtosis	-0.1478822814
Mean	-1.904723627
Median Absolute Deviation (MAD)	0.34447367
Skewness	0.1941627832
Sum	-140566.699
Variance	0.2482341863
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-1.77526279	352	0.5%
-2.22500363	296	0.4%
-2.1042109	288	0.4%
-2.16966378	258	0.3%
-1.92082293	185	0.3%
-2.02410005	180	0.2%
-2.38726804	169	0.2%
-1.52642194	145	0.2%
-2.44723899	142	0.2%
-2.35305175	116	0.2%
Other values (69086)	71668	97.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-3.62458632	1	< 0.1%
-3.59798083	1	< 0.1%
-3.58258691	1	< 0.1%
-3.52130561	1	< 0.1%
-3.51556161	1	< 0.1%
-3.49268613	1	< 0.1%
-3.4916199	1	< 0.1%
-3.48564255	1	< 0.1%
-3.45608632	3	< 0.1%
-3.45570913	1	< 0.1%

Value	Count	Frequency (%)
0.19977285	2	< 0.1%
0.1980699	1	< 0.1%
0.18361297	1	< 0.1%
0.16854933	1	< 0.1%
0.05603462	1	< 0.1%
0.04595876	1	< 0.1%
0.02390815	1	< 0.1%
0.0216169	1	< 0.1%
-0.00680477	1	< 0.1%
-0.01230332	1	< 0.1%

decline_app_cnt
Real number (ℝ_≥0)

ZEROS

Distinct	21
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.2757489939

Minimum	0
Maximum	33
Zeros	61214
Zeros (%)	82.9%
Negative	0
Negative (%)	0.0%
Memory size	1.1 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	2
Maximum	33
Range	33
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.8042721438
Coefficient of variation (CV)	2.916682061
Kurtosis	95.63484404
Mean	0.2757489939
Median Absolute Deviation (MAD)	0
Skewness	6.356795661
Sum	20350
Variance	0.6468536813
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=21)

Value	Count	Frequency (%)
0	61214	82.9%
1	8397	11.4%
2	2468	3.3%
3	903	1.2%
4	414	0.6%
5	165	0.2%
6	113	0.2%
7	48	0.1%
9	24	< 0.1%
8	19	< 0.1%
Other values (11)	34	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	61214	82.9%
1	8397	11.4%
2	2468	3.3%
3	903	1.2%
4	414	0.6%
5	165	0.2%
6	113	0.2%
7	48	0.1%
8	19	< 0.1%
9	24	< 0.1%

Value	Count	Frequency (%)
33	1	< 0.1%
24	1	< 0.1%
22	1	< 0.1%
19	1	< 0.1%
16	2	< 0.1%
15	1	< 0.1%
14	2	< 0.1%
13	3	< 0.1%
12	2	< 0.1%
11	9	< 0.1%

bki_request_cnt
Real number (ℝ_≥0)

ZEROS

Distinct	38
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.000338758

Minimum	0
Maximum	53
Zeros	19381
Zeros (%)	26.3%
Negative	0
Negative (%)	0.0%
Memory size	1.1 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	3
95-th percentile	6
Maximum	53
Range	53
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	2.252072623
Coefficient of variation (CV)	1.125845617
Kurtosis	22.92302298
Mean	2.000338758
Median Absolute Deviation (MAD)	1
Skewness	3.035199187
Sum	147623
Variance	5.0718311
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=38)

Value	Count	Frequency (%)
0	19381	26.3%
1	18276	24.8%
2	13749	18.6%
3	9187	12.4%
4	5627	7.6%
5	3268	4.4%
6	1704	2.3%
7	852	1.2%
8	508	0.7%
9	299	0.4%
Other values (28)	948	1.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	19381	26.3%
1	18276	24.8%
2	13749	18.6%
3	9187	12.4%
4	5627	7.6%
5	3268	4.4%
6	1704	2.3%
7	852	1.2%
8	508	0.7%
9	299	0.4%

Value	Count	Frequency (%)
53	1	< 0.1%
46	1	< 0.1%
45	1	< 0.1%
41	1	< 0.1%
36	1	< 0.1%
34	1	< 0.1%
33	1	< 0.1%
32	2	< 0.1%
29	1	< 0.1%
28	4	< 0.1%

income
Real number (ℝ_≥0)

Distinct	966
Distinct (%)	1.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	41099.77542

Minimum	1000
Maximum	1000000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 MiB

Quantile statistics

Minimum	1000
5-th percentile	10000
Q1	20000
median	30000
Q3	48000
95-th percentile	100000
Maximum	1000000
Range	999000
Interquartile range (IQR)	28000

Descriptive statistics

Standard deviation	46166.3224
Coefficient of variation (CV)	1.123274323
Kurtosis	104.0283418
Mean	41099.77542
Median Absolute Deviation (MAD)	12000
Skewness	7.702438065
Sum	3033122326
Variance	2131329324
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
30000	7009	9.5%
25000	6061	8.2%
20000	5471	7.4%
40000	4935	6.7%
50000	4470	6.1%
35000	4231	5.7%
15000	3949	5.4%
60000	2523	3.4%
45000	2486	3.4%
18000	1832	2.5%
Other values (956)	30832	41.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1000	5	< 0.1%
1100	1	< 0.1%
1500	2	< 0.1%
1700	1	< 0.1%
2000	1	< 0.1%
2400	2	< 0.1%
2450	1	< 0.1%
2500	1	< 0.1%
3000	4	< 0.1%
3073	1	< 0.1%

Value	Count	Frequency (%)
1000000	10	< 0.1%
999999	3	< 0.1%
999000	2	< 0.1%
990000	1	< 0.1%
950000	4	< 0.1%
947000	1	< 0.1%
900000	6	< 0.1%
850011	1	< 0.1%
830000	1	< 0.1%
800000	8	< 0.1%

age
Real number (ℝ_≥0)

Distinct	52
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	39.28064066

Minimum	21
Maximum	72
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 MiB

Quantile statistics

Minimum	21
5-th percentile	24
Q1	30
median	37
Q3	48
95-th percentile	60
Maximum	72
Range	51
Interquartile range (IQR)	18

Descriptive statistics

Standard deviation	11.5203779
Coefficient of variation (CV)	0.2932838595
Kurtosis	-0.7349138354
Mean	39.28064066
Median Absolute Deviation (MAD)	9
Skewness	0.4747453868
Sum	2898872
Variance	132.7191069
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
31	2727	3.7%
28	2705	3.7%
30	2693	3.6%
29	2659	3.6%
27	2645	3.6%
26	2528	3.4%
32	2501	3.4%
34	2395	3.2%
33	2314	3.1%
35	2259	3.1%
Other values (42)	48373	65.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
21	849	1.2%
22	937	1.3%
23	1509	2.0%
24	1873	2.5%
25	2202	3.0%
26	2528	3.4%
27	2645	3.6%
28	2705	3.7%
29	2659	3.6%
30	2693	3.6%

Value	Count	Frequency (%)
72	2	< 0.1%
71	3	< 0.1%
70	32	< 0.1%
69	81	0.1%
68	165	0.2%
67	248	0.3%
66	309	0.4%
65	422	0.6%
64	449	0.6%
63	477	0.6%

region_rating
Real number (ℝ_≥0)

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.672570089

Minimum	1
Maximum	7
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 MiB

Quantile statistics

Minimum	1
5-th percentile	3
Q1	4
median	4
Q3	5
95-th percentile	7
Maximum	7
Range	6
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.30557172
Coefficient of variation (CV)	0.2794119072
Kurtosis	-0.628301709
Mean	4.672570089
Median Absolute Deviation (MAD)	1
Skewness	0.4815443039
Sum	344831
Variance	1.704517516
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
4	27523	37.3%
5	16075	21.8%
3	12027	16.3%
7	11469	15.5%
6	6199	8.4%
2	300	0.4%
1	206	0.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	206	0.3%
2	300	0.4%
3	12027	16.3%
4	27523	37.3%
5	16075	21.8%
6	6199	8.4%
7	11469	15.5%

Value	Count	Frequency (%)
7	11469	15.5%
6	6199	8.4%
5	16075	21.8%
4	27523	37.3%
3	12027	16.3%
2	300	0.4%
1	206	0.3%

sna
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

1	47301
4	11749
2	10626
3	4123

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	73,799
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	4
2nd row	4
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	47301	64.1%
4	11749	15.9%
2	10626	14.4%
3	4123	5.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	47301	64.1%
4	11749	15.9%
2	10626	14.4%
3	4123	5.6%

Most occurring characters

Value	Count	Frequency (%)
1	47301	64.1%
4	11749	15.9%
2	10626	14.4%
3	4123	5.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	73799	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	47301	64.1%
4	11749	15.9%
2	10626	14.4%
3	4123	5.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	73799	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	47301	64.1%
4	11749	15.9%
2	10626	14.4%
3	4123	5.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	73799	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	47301	64.1%
4	11749	15.9%
2	10626	14.4%
3	4123	5.6%

first_time
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

3	31255
4	18737
1	12239
2	11568

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	73,799
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	4
4th row	3
5th row	4

Common Values

Value	Count	Frequency (%)
3	31255	42.4%
4	18737	25.4%
1	12239	16.6%
2	11568	15.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
3	31255	42.4%
4	18737	25.4%
1	12239	16.6%
2	11568	15.7%

Most occurring characters

Value	Count	Frequency (%)
3	31255	42.4%
4	18737	25.4%
1	12239	16.6%
2	11568	15.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	73799	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
3	31255	42.4%
4	18737	25.4%
1	12239	16.6%
2	11568	15.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	73799	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
3	31255	42.4%
4	18737	25.4%
1	12239	16.6%
2	11568	15.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	73799	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
3	31255	42.4%
4	18737	25.4%
1	12239	16.6%
2	11568	15.7%

education
Real number (ℝ_≥0)

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.823669697

Minimum	1
Maximum	6
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 MiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	2
median	2
Q3	4
95-th percentile	4
Maximum	6
Range	5
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	0.9594364793
Coefficient of variation (CV)	0.3397835378
Kurtosis	-1.177319922
Mean	2.823669697
Median Absolute Deviation (MAD)	0
Skewness	0.5168116357
Sum	208384
Variance	0.9205183578
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
2	38860	52.7%
4	23365	31.7%
3	9816	13.3%
5	1257	1.7%
1	307	0.4%
6	194	0.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	307	0.4%
2	38860	52.7%
3	9816	13.3%
4	23365	31.7%
5	1257	1.7%
6	194	0.3%

Value	Count	Frequency (%)
6	194	0.3%
5	1257	1.7%
4	23365	31.7%
3	9816	13.3%
2	38860	52.7%
1	307	0.4%

app_date
Date

Distinct	120
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

Minimum	2014-01-01 00:00:00
Maximum	2014-04-30 00:00:00

Histogram

Histogram with fixed size bins (bins=50)

good_work
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

0	61630
1	12169

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	73,799
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	61630	83.5%
1	12169	16.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	61630	83.5%
1	12169	16.5%

Most occurring characters

Value	Count	Frequency (%)
0	61630	83.5%
1	12169	16.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	73799	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	61630	83.5%
1	12169	16.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	73799	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	61630	83.5%
1	12169	16.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	73799	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	61630	83.5%
1	12169	16.5%

car
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

0	49832
1	23967

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	73,799
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	49832	67.5%
1	23967	32.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	49832	67.5%
1	23967	32.5%

Most occurring characters

Value	Count	Frequency (%)
0	49832	67.5%
1	23967	32.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	73799	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	49832	67.5%
1	23967	32.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	73799	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	49832	67.5%
1	23967	32.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	73799	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	49832	67.5%
1	23967	32.5%

car_type
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

0	59791
1	14008

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	73,799
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	59791	81.0%
1	14008	19.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	59791	81.0%
1	14008	19.0%

Most occurring characters

Value	Count	Frequency (%)
0	59791	81.0%
1	14008	19.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	73799	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	59791	81.0%
1	14008	19.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	73799	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	59791	81.0%
1	14008	19.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	73799	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	59791	81.0%
1	14008	19.0%

foreign_passport
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

0	62733
1	11066

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	73,799
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	62733	85.0%
1	11066	15.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	62733	85.0%
1	11066	15.0%

Most occurring characters

Value	Count	Frequency (%)
0	62733	85.0%
1	11066	15.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	73799	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	62733	85.0%
1	11066	15.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	73799	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	62733	85.0%
1	11066	15.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	73799	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	62733	85.0%
1	11066	15.0%

sex_male
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

0	41562
1	32237

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	73,799
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	1
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	41562	56.3%
1	32237	43.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	41562	56.3%
1	32237	43.7%

Most occurring characters

Value	Count	Frequency (%)
0	41562	56.3%
1	32237	43.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	73799	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	41562	56.3%
1	32237	43.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	73799	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	41562	56.3%
1	32237	43.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	73799	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	41562	56.3%
1	32237	43.7%

home_address_1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

0.0	41214
1.0	32585

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	221,397
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	0.0
3rd row	1.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	41214	55.8%
1.0	32585	44.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	41214	55.8%
1.0	32585	44.2%

Most occurring characters

Value	Count	Frequency (%)
0	115013	51.9%
.	73799	33.3%
1	32585	14.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	147598	66.7%
Other Punctuation	73799	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	115013	77.9%
1	32585	22.1%

Other Punctuation

Value	Count	Frequency (%)
.	73799	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	221397	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	115013	51.9%
.	73799	33.3%
1	32585	14.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	221397	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	115013	51.9%
.	73799	33.3%
1	32585	14.7%

home_address_2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

1.0	39956
0.0	33843

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	221,397
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	0.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	39956	54.1%
0.0	33843	45.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	39956	54.1%
0.0	33843	45.9%

Most occurring characters

Value	Count	Frequency (%)
0	107642	48.6%
.	73799	33.3%
1	39956	18.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	147598	66.7%
Other Punctuation	73799	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	107642	72.9%
1	39956	27.1%

Other Punctuation

Value	Count	Frequency (%)
.	73799	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	221397	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	107642	48.6%
.	73799	33.3%
1	39956	18.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	221397	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	107642	48.6%
.	73799	33.3%
1	39956	18.0%

home_address_3
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

0.0	72541
1.0	1258

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	221,397
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	72541	98.3%
1.0	1258	1.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	72541	98.3%
1.0	1258	1.7%

Most occurring characters

Value	Count	Frequency (%)
0	146340	66.1%
.	73799	33.3%
1	1258	0.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	147598	66.7%
Other Punctuation	73799	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	146340	99.1%
1	1258	0.9%

Other Punctuation

Value	Count	Frequency (%)
.	73799	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	221397	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	146340	66.1%
.	73799	33.3%
1	1258	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	221397	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	146340	66.1%
.	73799	33.3%
1	1258	0.6%

work_address_1
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

0.0	65465
1.0	8334

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	221,397
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	65465	88.7%
1.0	8334	11.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	65465	88.7%
1.0	8334	11.3%

Most occurring characters

Value	Count	Frequency (%)
0	139264	62.9%
.	73799	33.3%
1	8334	3.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	147598	66.7%
Other Punctuation	73799	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	139264	94.4%
1	8334	5.6%

Other Punctuation

Value	Count	Frequency (%)
.	73799	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	221397	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	139264	62.9%
.	73799	33.3%
1	8334	3.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	221397	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	139264	62.9%
.	73799	33.3%
1	8334	3.8%

work_address_2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

0.0	53293
1.0	20506

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	221,397
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	0.0
3rd row	1.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	53293	72.2%
1.0	20506	27.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	53293	72.2%
1.0	20506	27.8%

Most occurring characters

Value	Count	Frequency (%)
0	127092	57.4%
.	73799	33.3%
1	20506	9.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	147598	66.7%
Other Punctuation	73799	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	127092	86.1%
1	20506	13.9%

Other Punctuation

Value	Count	Frequency (%)
.	73799	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	221397	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	127092	57.4%
.	73799	33.3%
1	20506	9.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	221397	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	127092	57.4%
.	73799	33.3%
1	20506	9.3%

work_address_3
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

1.0	44959
0.0	28840

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	221,397
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	0.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	44959	60.9%
0.0	28840	39.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	44959	60.9%
0.0	28840	39.1%

Most occurring characters

Value	Count	Frequency (%)
0	102639	46.4%
.	73799	33.3%
1	44959	20.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	147598	66.7%
Other Punctuation	73799	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	102639	69.5%
1	44959	30.5%

Other Punctuation

Value	Count	Frequency (%)
.	73799	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	221397	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	102639	46.4%
.	73799	33.3%
1	44959	20.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	221397	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	102639	46.4%
.	73799	33.3%
1	44959	20.3%

default
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

0	64427
1	9372

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	73,799
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	64427	87.3%
1	9372	12.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	64427	87.3%
1	9372	12.7%

Most occurring characters

Value	Count	Frequency (%)
0	64427	87.3%
1	9372	12.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	73799	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	64427	87.3%
1	9372	12.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	73799	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	64427	87.3%
1	9372	12.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	73799	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	64427	87.3%
1	9372	12.7%

sample
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

1	73799

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	73,799
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	73799	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	73799	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	73799	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	73799	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	73799	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	73799	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	73799	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	73799	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	73799	100.0%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	client_id	score_bki	decline_app_cnt	bki_request_cnt	income	age	region_rating	sna	first_time	education	app_date	good_work	car	car_type	foreign_passport	sex_male	home_address_1	home_address_2	work_address_1	work_address_2	work_address_3	sample
0	25905	-2.008753	0	1	18000	62	4	4	1	2	2014-02-01	0	1	1	0	1	1.0	0.0	0.0	1.0	0.0	1
1	63161	-1.532276	0	3	19000	59	4	4	1	2	2014-03-12	0	0	0	0	0	0.0	1.0	0.0	0.0	1.0	1
2	25887	-1.408142	2	1	30000	25	7	1	4	2	2014-02-01	0	1	0	1	1	1.0	0.0	0.0	1.0	0.0	1
3	16222	-2.057471	0	2	10000	53	4	1	3	2	2014-01-23	0	0	0	0	0	0.0	1.0	0.0	0.0	1.0	1
4	101655	-1.244723	0	1	30000	48	5	1	4	4	2014-04-18	1	0	0	1	1	0.0	1.0	0.0	0.0	1.0	1
5	41415	-2.032257	0	0	15000	27	4	2	3	2	2014-02-18	1	1	0	0	1	1.0	0.0	1.0	0.0	0.0	1
6	28436	-2.225004	0	0	28000	39	5	1	1	2	2014-02-04	0	0	0	0	1	1.0	0.0	0.0	1.0	0.0	1
7	68769	-1.522739	0	1	45000	39	4	3	3	2	2014-03-17	0	0	0	0	0	0.0	1.0	0.0	0.0	1.0	1
8	38424	-1.676061	1	0	30000	50	4	1	4	2	2014-02-14	0	1	0	0	0	1.0	0.0	1.0	0.0	0.0	1
9	4496	-2.695176	0	1	24000	54	4	1	3	3	2014-01-10	0	0	0	0	0	0.0	1.0	0.0	0.0	1.0	1

Last rows

	client_id	score_bki	bki_request_cnt	income	age	region_rating	sna	first_time	education	app_date	good_work	car	car_type	foreign_passport	sex_male	home_address_1	home_address_2	work_address_1	work_address_2	work_address_3	default	sample
73789	44132	-1.662674	0	25000	40	4	4	3	3	2014-02-20	0	0	0	0	1	0.0	1.0	0.0	1.0	0.0	0	1
73790	87499	-1.601775	1	100600	24	5	1	4	4	2014-04-03	0	1	1	0	1	1.0	0.0	1.0	0.0	0.0	0	1
73791	37195	-1.077492	2	90000	54	6	1	3	2	2014-02-13	0	1	0	0	0	1.0	0.0	0.0	1.0	0.0	0	1
73792	82387	-2.157530	1	45000	37	7	1	2	3	2014-03-30	0	1	0	1	0	0.0	1.0	0.0	0.0	1.0	0	1
73793	6266	-1.470891	0	35000	48	7	1	4	2	2014-01-13	0	0	0	1	0	0.0	1.0	0.0	0.0	1.0	0	1
73794	54887	-1.792064	3	17000	45	4	4	4	4	2014-03-04	0	0	0	0	0	1.0	0.0	0.0	1.0	0.0	0	1
73795	76821	-2.058029	1	70000	41	4	1	4	2	2014-03-24	0	1	1	0	1	0.0	1.0	0.0	1.0	0.0	0	1
73796	103695	-1.512635	4	45000	31	7	2	2	2	2014-04-22	0	0	0	0	1	0.0	1.0	0.0	0.0	1.0	0	1
73797	861	-1.479334	3	13000	29	4	2	3	2	2014-01-04	1	0	0	0	0	1.0	0.0	0.0	0.0	1.0	1	1
73798	15796	-1.764711	2	25000	34	4	1	3	4	2014-01-23	0	0	0	0	1	0.0	1.0	0.0	0.0	1.0	0	1

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII